Cannon Studio

Search Cannon Studio Knowledge

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Read-onlyIdempotent

Search public Cannon Studio knowledge when a user asks about products, workflows, pricing, models, comparisons, use cases, or developer API docs. Public read-only: no auth, no state changes, no charges; call fetch with a returned id when full source-backed text is needed.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of results. Defaults to 8 and caps at 20.
`query`	Yes	Natural-language query to search Cannon Studio public knowledge.
`audience`	No	Optional audience/persona filter such as creators, agencies, marketing teams, or developers.
`category`	No	Optional category filter such as pricing, developer, comparison, model_availability, use_case, tools, or creator_flow.
`pain_point`	No	Optional pain point filter such as consistent characters, cost predictability, team review, model choice, or finishing.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`results`	Yes

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate a safe read-only operation; the description adds 'no auth, no state changes, no charges' and explains that returned ids can be used with fetch for full text, revealing that search results may not be complete documents. This goes beyond what annotations and schema provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first states purpose and usage triggers, second discloses safety and follow-up action. No redundant phrases, highly scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, usage context, safety profile, and relationship to fetch, while the output schema documents return structure. This is sufficient for a read-only search tool with a rich schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all five parameters are documented in the input schema. The description itself doesn't elaborate on individual parameters but does contextualize the query parameter as natural-language over public knowledge. Baseline 3 is appropriate when the schema carries the parameter detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Search public Cannon Studio knowledge' with a specific verb and resource. It lists common query types (products, workflows, pricing, models, comparisons, use cases, developer API docs), distinguishing it from sibling tools like fetch which retrieves full text by id.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies when to use the tool ('when a user asks about...') and explicitly directs to 'call fetch with a returned id when full source-backed text is needed', providing clear guidance on an alternative. It doesn't enumerate all sibling alternatives, but the context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct resource or action: status, comparison, creation, estimation, fetching, API docs, checkout, generation polling, model availability, pricing, capabilities, offerings, toolkits, workflow recommendation, and knowledge search. Even the get_* and list_* tools have clear, non-overlapping purposes.

Naming Consistency3/5

Most tools follow a verb_noun pattern (create_generation_request, list_offerings, get_checkout_link), but there are exceptions: api_status is a noun, and fetch and search are single verbs without an object. The mix of get/list/compare/recommend/search/fetch is readable but not perfectly uniform.

Tool Count5/5

15 tools is at the upper bound of the well-scoped range, but each tool serves a clear, distinct purpose in the Cannon Studio domain—from estimation and creation to knowledge retrieval and workflow recommendation. No tool feels redundant or superfluous.

Completeness3/5

The surface covers creation, estimation, polling, knowledge, and commercial operations, but the generation lifecycle is incomplete: there is no update, cancel, or list tool for generation requests, and the create tool explicitly cannot be cancelled through MCP. This is a notable gap for agents managing ongoing work.

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